Researchers have developed a machine learning model called LeSeTS to predict the properties of high-entropy alloys by capturing local atomic interactions in disordered materials. This breakthrough allows for more accurate predictions of these alloys’ mechanical and thermal properties, which are challenging due to their complex atomic structures. The model leverages local environments and atomic-scale features, representing a significant advance in materials science and design, enabling faster development of durable, high-performance alloys for industrial applications.
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